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Long-term coupled permafrost-groundwater interactions at Olkiluoto, Finland

2020· article· en· W3131641162 on OpenAlexaff
Denis Cohen, Thomas Zwinger, Lasse Koskinen, Tuomo Karvonen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsPricewaterhouseCoopers (Canada)
Fundersnot available
KeywordsSpan (engineering)ChemistryEngineering

Abstract

fetched live from OpenAlex

Understanding permafrost development and its effect on groundwater flow patterns and fluxes in the event of future ice-age conditions is important for the long-term safety of spent nuclear fuel repositories. To assess the evolution of permafrost thickness, talik development, and groundwater flow and salinity changes at Olkiluoto, Finland, during the next 100,000 years, we solve Darcy flow coupled to heat and solute transport in three dimensions in a rectangular block representing an area of 8.8 km by 6.8 km, and down to a depth of 10 km. The set of equations is based on continuum thermo-mechanic principles. Important and highly non-linear coupling processes such as the exponential decrease of permeability with ice content in soils and rocks, solute rejection during freezing, and variable-density Darcy flow are fully taken into account. Model equations are solved using the finite element method implemented in the open source software Elmer. High-resolution data of rock and soil permeability, thermal and physical properties, are mapped onto a 30-meter resolution grid resulting in a system of about 5 million nodes and 5 million elements. Soil layers at the surface are vertically resolved down to 0.1 meter. High contrast in permeability over short distances (from soil to granitic bedrock) make the system of equations challenging to solve numerically. Simulations are driven by RCP 4.5 climate scenario that predicts cold periods between AD 47,000 and AD 110,000. Surface boundary condition for temperature is calculated based on freezing and thawing n-factors that depend on monthly temperatures and the topographic wetness index that defines different zones of vegetation and ground cover. The thickness evolution of the six upper soil layers, including peat, above the granitic bedrock is also taken into account. Preliminary simulations are able to represent permafrost development at a high spatial resolution with evidence of important feedbacks due to permeable soil layers and faults in the bedrock that focus groundwater flow and solute transport.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.258
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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